Recent years have witnessed an explosive increase in data traffic of mobile communication with rapid wide-spread use of smartphones and tablet terminals, and the like. For example, at the 2007 World Wireless Conference (WRC-07 (World Radiocommunication Conference 2007)), an international agreement has been made by securing 3.5 GHz (Giga Hertz) band or the like as a frequency band for 4G (4th Generation) such as LTE (Long Term Evolution)-Advanced. In the future, in order to cope with traffic explosion, it is expected that these new frequency bands will be allocated for 4G and next 5G (5th Generation).
In addition, in order to increase a traffic capacity of an entire system, a heterogeneous network configuration in which a plurality of small cell base stations are installed in an area of a macro cell base station, a high density installation of small cell base stations, improvement of frequency utilization efficiency by advanced MIMO (Multi-Input Multi-Output) technology with a multi-element antenna (Massive MIMO), and so forth are under study. Furthermore, a movement towards a next generation, i.e., the 5th generation mobile communication standard (5G) has become active, such as an establishment of related promotion groups in each country. In the future, it is expected that applications that transmit and receive video data at a high bit rate will increase.
In order to accommodate an increase in traffic for each user, in particular, a beamforming technique for an individual user by multi-user MIMO (MU-MIMO) using multi-element antennas, is drawing attention. For example, beam formation is individually performed in a direction of a selected path using a multi-element antenna (antenna array). By using this technique, improvement of frequency utilization efficiency is expected by increasing a spatial multiplexing number in one base station cell.
Traffic for each radio base station may change from time to time, depending on, for example, an installation location of a radio base station. For example, in a case where a radio base station is installed in an office area, a traffic peak appears in a daytime which is a working time zone. In a case where a radio base station is installed in a residential area, a traffic peak appears from evening to night after a subscriber returning home. In either area, traffic usually decreases at midnight.
On the other hand, even in the same area, assuming a configuration in which a plurality of small cell base stations are installed at a high density in the area, when one or more users move in the area, the number of users served by the small cell base station with a small cell radii and an amount of accommodated traffic are largely fluctuated with time.
Therefore, a dynamic cell formation technology (cell virtualization) that dynamically changes a cell size and shape by beam forming or the like according to extent of fluctuation of user density (traffic density) for each small cell base station, etc., is also under consideration. The dynamic cell formation technology dynamically performs load balancing of users and traffic served and accommodated by each of small cell base station, as a result of which a capacity that can be accommodated as a whole is improved.
As standard beamforming, for example, in standards based on 3GPP (Third Generation Partnership Project) (3GPP TS 36.211, 3GPP 36.213, etc.), and in IEEE 802.11n, the subsequent 802.11ac, or the like, which is the standard of a wireless LAN (Local Area Network) established by IEEE (Institute of Electrical and Electronics Engineers, Inc), the following approach is assumed (an example in a case of transmission).
(a) Steering antennas in all directions within a cell/sector of a base station,
searching for terminal location (direction), and
calculating a precoding weight from an obtained steering angle.
(b) Calculating a precoding weight by matrix calculation on a side of a base station which has an estimated value of a propagation path (channel) that a terminal obtains, sent thereto
(c) When using the same frequency band in uplink and downlink (in a case of TDD (Time Division Duplex)), a known signal is transmitted from a terminal to the base station which estimates a transmission path (channel) to calculate a precoding weight using matrix operation.
The following describes an outline of an example of a precoding weight in LTE MU-MIMO and the like with reference to FIG. 16. In the LTE MU-MIMO, transmission information sequences destined for the terminals 1 of a plurality of users are simultaneously transmitted from different transmission antennas (#1 to #N) of the base station (evolved Node B: eNode B) 110. In the terminal 1, a channel estimation unit 11 estimates a channel from the signal transmitted from the base station 110. Then, for example, a PMI selector 12 selects an optimum PMI from the book in which a phase/amplitude control amount to be set to the antenna of the base station (a precoding matrix) and a plurality of PMIs (Precoding Matrix Indicators) associated with this precoding matrix are stored in advance. The terminal 1 feeds back the selected PMI, for example, as channel information (Channel State Information: CSI) to the base station 110. In the base station 110, a precoding weight generation unit 111 generates a precoding weight for each transmission antenna based on the PMI fed back from the terminal 1 and sets precoding weight as coefficients of a precoding matrix of a precoder 112. In FIGS. 16, H1 and H2 represent MIMO channel matrix (M×N) between base station antennas and terminal antennas. The number M of antennas of the terminal and the number N of antennas of the base station may be the same.
It is known that there is a problem in the approaches of related technology of the above (a), (b) and (c):
It takes time for search processing; and
Computation of precoding weight is complicated.
In the case of the configuration described with reference to FIG. 16, although a calculation amount of the precoding weight can be suppressed, there is a problem that, for example, the number of code books becomes large as the number of antennas increases.
For example, in the case of the approach (a), it is necessary to perform communication by steering antennas in all directions in a cell/sector, in order. For this reason, a trial time corresponding to the number of steering times is required for searching a location of a terminal (direction).
In the case of the approaches (b) and (c), a location of a terminal is not grasped, but a precoding weight from an estimated value of a propagation path (channel) is calculated by matrix operation. Therefore, if the number of antennas or the number of users performing spatial multiplexing is increased, calculation of the precoding weight is complicated. In order to improve accuracy, more complicated calculation is required.
Also, in the case of the approach (a), when using antennas with high directivity such as millimeter waves, the base station cannot receive information from a terminal(s) to which the base station cannot set direction of antennas thereof. For this reason, on the side of the base station, there are cases where even the direction to which the antenna should be directed is not known.
Similarly, in the case of the approaches (b) and (c), once a cell shape is made smaller by dynamic cell formation, there may be a case in which information on a propagation path (channel estimation) cannot be obtained from a terminal outside the cell range.
In recent years, in data processing (hereinafter referred to as “IT (Information Technology) processing” by an information processing system such as a server, an application requiring a large amount of data processing obtained by big data and M2M (Machine to Machine) communication has attracted attention.
As a specific example, there is an image recognition technology for autonomously recognizing a face of a person or an object by image processing of an image acquired by a surveillance camera. For example, a suspicious person monitoring system or the like that automatically registers face information of criminals or suspicious individuals as a black list and automatically detects a suspicious individual by face authentication/face collation processing using a surveillance camera image is expected.
In addition, such a system is expected that a mechanism for continuously tracking and following a detected suspicious individual(s), or a mechanism for identifying an ID of a target mobile terminal detected for identifying a suspicious individual, blocking communication of the terminal, grasping a terminal acquisition route, or the like is implemented. Through these mechanisms, it is considered good to early secure criminals and prevent crime. In this way, applications using cameras and images are expected to increase. It is conceived that usage in other fields other than the above will become common.
As a method of controlling an antenna of a wireless communication apparatus in combination with a camera image, there is known a technique in which a user location is grasped by image processing of the camera image, and the antenna is controlled so as to include the user location. For example, Patent Literature 1 discloses a technique of controlling an antenna of a wireless communication apparatus in combination with a camera image by photographing an image of a space to be a target of wireless communication with a camera, an image acquisition unit acquires a user location of a wireless communication terminal and changes a directivity of the antenna so as to include the specified user location. Patent Literature 1 describes that unexpected leakage and interference of transmitted radio waves can be suppressed.
[Patent Literature 1]
JP patent Kokai Publication No. JP2013-51570A